{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Importing plotly failed. Interactive plots will not work.\n"
     ]
    }
   ],
   "source": [
    "import tushare as ts\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "import datetime\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "register_matplotlib_converters()\n",
    "sns.set_style('darkgrid')\n",
    "plt.rc('figure',figsize=(16,12))\n",
    "plt.rc('font',size=13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20201021</td>\n",
       "      <td>23.33</td>\n",
       "      <td>25.33</td>\n",
       "      <td>22.08</td>\n",
       "      <td>22.52</td>\n",
       "      <td>23.45</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>-3.9659</td>\n",
       "      <td>636139.90</td>\n",
       "      <td>1529210.565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20201020</td>\n",
       "      <td>21.00</td>\n",
       "      <td>23.45</td>\n",
       "      <td>20.93</td>\n",
       "      <td>23.45</td>\n",
       "      <td>21.32</td>\n",
       "      <td>2.13</td>\n",
       "      <td>9.9906</td>\n",
       "      <td>544230.34</td>\n",
       "      <td>1222651.067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20201019</td>\n",
       "      <td>20.36</td>\n",
       "      <td>21.88</td>\n",
       "      <td>19.88</td>\n",
       "      <td>21.32</td>\n",
       "      <td>20.00</td>\n",
       "      <td>1.32</td>\n",
       "      <td>6.6000</td>\n",
       "      <td>438082.48</td>\n",
       "      <td>915667.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20201016</td>\n",
       "      <td>19.80</td>\n",
       "      <td>20.16</td>\n",
       "      <td>19.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>19.65</td>\n",
       "      <td>0.35</td>\n",
       "      <td>1.7812</td>\n",
       "      <td>255767.00</td>\n",
       "      <td>503166.172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20201015</td>\n",
       "      <td>18.54</td>\n",
       "      <td>20.21</td>\n",
       "      <td>18.09</td>\n",
       "      <td>19.65</td>\n",
       "      <td>19.00</td>\n",
       "      <td>0.65</td>\n",
       "      <td>3.4211</td>\n",
       "      <td>281420.99</td>\n",
       "      <td>542724.059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20200323</td>\n",
       "      <td>13.20</td>\n",
       "      <td>13.63</td>\n",
       "      <td>12.83</td>\n",
       "      <td>13.21</td>\n",
       "      <td>12.68</td>\n",
       "      <td>0.53</td>\n",
       "      <td>4.1798</td>\n",
       "      <td>553142.51</td>\n",
       "      <td>733068.643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20200320</td>\n",
       "      <td>12.74</td>\n",
       "      <td>14.12</td>\n",
       "      <td>12.51</td>\n",
       "      <td>12.68</td>\n",
       "      <td>13.90</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>-8.7770</td>\n",
       "      <td>667692.82</td>\n",
       "      <td>869770.927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20200319</td>\n",
       "      <td>15.28</td>\n",
       "      <td>15.28</td>\n",
       "      <td>13.90</td>\n",
       "      <td>13.90</td>\n",
       "      <td>15.44</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>-9.9741</td>\n",
       "      <td>620578.46</td>\n",
       "      <td>886661.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20200318</td>\n",
       "      <td>15.40</td>\n",
       "      <td>15.44</td>\n",
       "      <td>14.58</td>\n",
       "      <td>15.44</td>\n",
       "      <td>14.04</td>\n",
       "      <td>1.40</td>\n",
       "      <td>9.9715</td>\n",
       "      <td>745276.83</td>\n",
       "      <td>1132273.046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>002581.SZ</td>\n",
       "      <td>20200317</td>\n",
       "      <td>13.19</td>\n",
       "      <td>14.04</td>\n",
       "      <td>12.38</td>\n",
       "      <td>14.04</td>\n",
       "      <td>12.76</td>\n",
       "      <td>1.28</td>\n",
       "      <td>10.0313</td>\n",
       "      <td>613276.26</td>\n",
       "      <td>829407.689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
       "0    002581.SZ   20201021  23.33  25.33  22.08  22.52      23.45   -0.93   \n",
       "1    002581.SZ   20201020  21.00  23.45  20.93  23.45      21.32    2.13   \n",
       "2    002581.SZ   20201019  20.36  21.88  19.88  21.32      20.00    1.32   \n",
       "3    002581.SZ   20201016  19.80  20.16  19.00  20.00      19.65    0.35   \n",
       "4    002581.SZ   20201015  18.54  20.21  18.09  19.65      19.00    0.65   \n",
       "..         ...        ...    ...    ...    ...    ...        ...     ...   \n",
       "140  002581.SZ   20200323  13.20  13.63  12.83  13.21      12.68    0.53   \n",
       "141  002581.SZ   20200320  12.74  14.12  12.51  12.68      13.90   -1.22   \n",
       "142  002581.SZ   20200319  15.28  15.28  13.90  13.90      15.44   -1.54   \n",
       "143  002581.SZ   20200318  15.40  15.44  14.58  15.44      14.04    1.40   \n",
       "144  002581.SZ   20200317  13.19  14.04  12.38  14.04      12.76    1.28   \n",
       "\n",
       "     pct_chg        vol       amount  \n",
       "0    -3.9659  636139.90  1529210.565  \n",
       "1     9.9906  544230.34  1222651.067  \n",
       "2     6.6000  438082.48   915667.188  \n",
       "3     1.7812  255767.00   503166.172  \n",
       "4     3.4211  281420.99   542724.059  \n",
       "..       ...        ...          ...  \n",
       "140   4.1798  553142.51   733068.643  \n",
       "141  -8.7770  667692.82   869770.927  \n",
       "142  -9.9741  620578.46   886661.475  \n",
       "143   9.9715  745276.83  1132273.046  \n",
       "144  10.0313  613276.26   829407.689  \n",
       "\n",
       "[145 rows x 11 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pro = ts.pro_api(token='*')\n",
    "start_time = datetime.date.today() + datetime.timedelta(-365*0.6)\n",
    "df = pro.daily(ts_code='002581.SZ', start_date=start_time.strftime(\"%Y%m%d\"))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>20200317</td>\n",
       "      <td>13.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>20200318</td>\n",
       "      <td>15.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>20200319</td>\n",
       "      <td>15.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>20200320</td>\n",
       "      <td>12.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>20200323</td>\n",
       "      <td>13.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20201015</td>\n",
       "      <td>18.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20201016</td>\n",
       "      <td>19.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20201019</td>\n",
       "      <td>20.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20201020</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20201021</td>\n",
       "      <td>23.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    trade_date   open\n",
       "144   20200317  13.19\n",
       "143   20200318  15.40\n",
       "142   20200319  15.28\n",
       "141   20200320  12.74\n",
       "140   20200323  13.20\n",
       "..         ...    ...\n",
       "4     20201015  18.54\n",
       "3     20201016  19.80\n",
       "2     20201019  20.36\n",
       "1     20201020  21.00\n",
       "0     20201021  23.33\n",
       "\n",
       "[145 rows x 2 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data = df[['trade_date','open']]\n",
    "# df_data = df_data.set_index('trade_date')\n",
    "df_data = df_data.sort_values('trade_date')\n",
    "df_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from statsmodels.tsa.seasonal import STL\n",
    "# stl = STL(df_data, seasonal=13)\n",
    "# res = stl.fit()\n",
    "# fig = res.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>20200317</td>\n",
       "      <td>13.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>20200318</td>\n",
       "      <td>15.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>20200319</td>\n",
       "      <td>15.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>20200320</td>\n",
       "      <td>12.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>20200323</td>\n",
       "      <td>13.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20201015</td>\n",
       "      <td>18.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20201016</td>\n",
       "      <td>19.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20201019</td>\n",
       "      <td>20.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20201020</td>\n",
       "      <td>21.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20201021</td>\n",
       "      <td>23.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds      y\n",
       "144  20200317  13.19\n",
       "143  20200318  15.40\n",
       "142  20200319  15.28\n",
       "141  20200320  12.74\n",
       "140  20200323  13.20\n",
       "..        ...    ...\n",
       "4    20201015  18.54\n",
       "3    20201016  19.80\n",
       "2    20201019  20.36\n",
       "1    20201020  21.00\n",
       "0    20201021  23.33\n",
       "\n",
       "[145 rows x 2 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data.rename(columns={'trade_date': 'ds', 'open': 'y'}, inplace=True)\n",
    "df_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x17b2dc8e3a0>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prophet = Prophet(daily_seasonality=True)\n",
    "prophet.fit(df_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'20201022'"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.date.today().strftime(\"%Y%m%d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'20201023'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(datetime.date.today()+datetime.timedelta(1)).strftime(\"%Y%m%d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['20201022', '20201023', '20201024', '20201025', '20201026']"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_list = []\n",
    "for i in range(5):\n",
    "    date_list.append((datetime.date.today()+datetime.timedelta(i)).strftime(\"%Y%m%d\"))\n",
    "date_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-03-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2020-10-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2020-10-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2020-10-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2020-10-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2020-10-26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds\n",
       "0   2020-03-17\n",
       "1   2020-03-18\n",
       "2   2020-03-19\n",
       "3   2020-03-20\n",
       "4   2020-03-23\n",
       "..         ...\n",
       "145 2020-10-22\n",
       "146 2020-10-23\n",
       "147 2020-10-24\n",
       "148 2020-10-25\n",
       "149 2020-10-26\n",
       "\n",
       "[150 rows x 1 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# future = prophet.make_future_dataframe(periods=365)\n",
    "future = prophet.make_future_dataframe(periods=5)\n",
    "future\n",
    "\n",
    "# future = pd.DataFrame({'ds': date_list})\n",
    "# future"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>daily</th>\n",
       "      <th>daily_lower</th>\n",
       "      <th>daily_upper</th>\n",
       "      <th>weekly</th>\n",
       "      <th>weekly_lower</th>\n",
       "      <th>weekly_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>12.903578</td>\n",
       "      <td>9.234064</td>\n",
       "      <td>15.151819</td>\n",
       "      <td>12.903578</td>\n",
       "      <td>12.903578</td>\n",
       "      <td>-0.800237</td>\n",
       "      <td>-0.800237</td>\n",
       "      <td>-0.800237</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>0.177155</td>\n",
       "      <td>0.177155</td>\n",
       "      <td>0.177155</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.103341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-18</td>\n",
       "      <td>13.101599</td>\n",
       "      <td>9.171146</td>\n",
       "      <td>15.197618</td>\n",
       "      <td>13.101599</td>\n",
       "      <td>13.101599</td>\n",
       "      <td>-0.721552</td>\n",
       "      <td>-0.721552</td>\n",
       "      <td>-0.721552</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>0.255840</td>\n",
       "      <td>0.255840</td>\n",
       "      <td>0.255840</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.380047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>13.299620</td>\n",
       "      <td>9.373817</td>\n",
       "      <td>15.204732</td>\n",
       "      <td>13.299620</td>\n",
       "      <td>13.299620</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.099134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>13.497641</td>\n",
       "      <td>9.091084</td>\n",
       "      <td>15.111617</td>\n",
       "      <td>13.497641</td>\n",
       "      <td>13.497641</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.173229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-23</td>\n",
       "      <td>14.091705</td>\n",
       "      <td>9.836108</td>\n",
       "      <td>16.056964</td>\n",
       "      <td>14.091705</td>\n",
       "      <td>14.091705</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.007085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2020-10-22</td>\n",
       "      <td>18.484871</td>\n",
       "      <td>14.180716</td>\n",
       "      <td>20.509693</td>\n",
       "      <td>18.484871</td>\n",
       "      <td>18.484871</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-1.200486</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>-0.223094</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.284385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2020-10-23</td>\n",
       "      <td>18.410615</td>\n",
       "      <td>14.004354</td>\n",
       "      <td>19.985052</td>\n",
       "      <td>18.410453</td>\n",
       "      <td>18.410645</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-1.324412</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>-0.347020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.086203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2020-10-24</td>\n",
       "      <td>18.336360</td>\n",
       "      <td>14.345282</td>\n",
       "      <td>20.421423</td>\n",
       "      <td>18.331529</td>\n",
       "      <td>18.341800</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.481142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2020-10-25</td>\n",
       "      <td>18.262104</td>\n",
       "      <td>14.577449</td>\n",
       "      <td>20.394849</td>\n",
       "      <td>18.249423</td>\n",
       "      <td>18.274926</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.855218</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.122174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.406886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2020-10-26</td>\n",
       "      <td>18.187849</td>\n",
       "      <td>14.149385</td>\n",
       "      <td>20.033377</td>\n",
       "      <td>18.166062</td>\n",
       "      <td>18.209374</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-1.084620</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.977392</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>-0.107228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.103229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds      trend  yhat_lower  yhat_upper  trend_lower  trend_upper  \\\n",
       "0   2020-03-17  12.903578    9.234064   15.151819    12.903578    12.903578   \n",
       "1   2020-03-18  13.101599    9.171146   15.197618    13.101599    13.101599   \n",
       "2   2020-03-19  13.299620    9.373817   15.204732    13.299620    13.299620   \n",
       "3   2020-03-20  13.497641    9.091084   15.111617    13.497641    13.497641   \n",
       "4   2020-03-23  14.091705    9.836108   16.056964    14.091705    14.091705   \n",
       "..         ...        ...         ...         ...          ...          ...   \n",
       "145 2020-10-22  18.484871   14.180716   20.509693    18.484871    18.484871   \n",
       "146 2020-10-23  18.410615   14.004354   19.985052    18.410453    18.410645   \n",
       "147 2020-10-24  18.336360   14.345282   20.421423    18.331529    18.341800   \n",
       "148 2020-10-25  18.262104   14.577449   20.394849    18.249423    18.274926   \n",
       "149 2020-10-26  18.187849   14.149385   20.033377    18.166062    18.209374   \n",
       "\n",
       "     additive_terms  additive_terms_lower  additive_terms_upper     daily  \\\n",
       "0         -0.800237             -0.800237             -0.800237 -0.977392   \n",
       "1         -0.721552             -0.721552             -0.721552 -0.977392   \n",
       "2         -1.200486             -1.200486             -1.200486 -0.977392   \n",
       "3         -1.324412             -1.324412             -1.324412 -0.977392   \n",
       "4         -1.084620             -1.084620             -1.084620 -0.977392   \n",
       "..              ...                   ...                   ...       ...   \n",
       "145       -1.200486             -1.200486             -1.200486 -0.977392   \n",
       "146       -1.324412             -1.324412             -1.324412 -0.977392   \n",
       "147       -0.855218             -0.855218             -0.855218 -0.977392   \n",
       "148       -0.855218             -0.855218             -0.855218 -0.977392   \n",
       "149       -1.084620             -1.084620             -1.084620 -0.977392   \n",
       "\n",
       "     daily_lower  daily_upper    weekly  weekly_lower  weekly_upper  \\\n",
       "0      -0.977392    -0.977392  0.177155      0.177155      0.177155   \n",
       "1      -0.977392    -0.977392  0.255840      0.255840      0.255840   \n",
       "2      -0.977392    -0.977392 -0.223094     -0.223094     -0.223094   \n",
       "3      -0.977392    -0.977392 -0.347020     -0.347020     -0.347020   \n",
       "4      -0.977392    -0.977392 -0.107228     -0.107228     -0.107228   \n",
       "..           ...          ...       ...           ...           ...   \n",
       "145    -0.977392    -0.977392 -0.223094     -0.223094     -0.223094   \n",
       "146    -0.977392    -0.977392 -0.347020     -0.347020     -0.347020   \n",
       "147    -0.977392    -0.977392  0.122174      0.122174      0.122174   \n",
       "148    -0.977392    -0.977392  0.122174      0.122174      0.122174   \n",
       "149    -0.977392    -0.977392 -0.107228     -0.107228     -0.107228   \n",
       "\n",
       "     multiplicative_terms  multiplicative_terms_lower  \\\n",
       "0                     0.0                         0.0   \n",
       "1                     0.0                         0.0   \n",
       "2                     0.0                         0.0   \n",
       "3                     0.0                         0.0   \n",
       "4                     0.0                         0.0   \n",
       "..                    ...                         ...   \n",
       "145                   0.0                         0.0   \n",
       "146                   0.0                         0.0   \n",
       "147                   0.0                         0.0   \n",
       "148                   0.0                         0.0   \n",
       "149                   0.0                         0.0   \n",
       "\n",
       "     multiplicative_terms_upper       yhat  \n",
       "0                           0.0  12.103341  \n",
       "1                           0.0  12.380047  \n",
       "2                           0.0  12.099134  \n",
       "3                           0.0  12.173229  \n",
       "4                           0.0  13.007085  \n",
       "..                          ...        ...  \n",
       "145                         0.0  17.284385  \n",
       "146                         0.0  17.086203  \n",
       "147                         0.0  17.481142  \n",
       "148                         0.0  17.406886  \n",
       "149                         0.0  17.103229  \n",
       "\n",
       "[150 rows x 19 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast = prophet.predict(future)\n",
    "forecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prophet.plot(forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
